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» Parallelizing Feature Selection
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ICML
1998
IEEE
14 years 8 months ago
Feature Selection via Concave Minimization and Support Vector Machines
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
Paul S. Bradley, Olvi L. Mangasarian
IEEEPACT
2008
IEEE
14 years 1 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
JSS
2010
136views more  JSS 2010»
13 years 2 months ago
Automated diagnosis of feature model configurations
Software product-lines (SPLs) are software architectures that can be readily reconfigured for different project requirements. A key part of an SPL is a model that captures the rul...
Jules White, David Benavides, Douglas C. Schmidt, ...
SYNASC
2005
IEEE
77views Algorithms» more  SYNASC 2005»
14 years 28 days ago
On P Systems with Bounded Parallelism
— A framework that describes the evolution of P systems with bounded parallelism is defined by introducing basic formal features that can be then integrated into a structural op...
Francesco Bernardini, Francisco José Romero...
ICDAR
2003
IEEE
14 years 19 days ago
Proper Names Extraction from Fax Images Combining Textual and Image Features
In the frame of a Unified Messaging System, a crucial task of the system is to provide the user with key information on every message received, like keywords reflecting the object...
Laurence Likforman-Sulem, Pascal Vaillant, Fran&cc...